Multimodal fusion of EMG and vision for human grasp intent inference in prosthetic hand control

Multimodal fusion of EMG and vision for human grasp intent inference in prosthetic hand control

Objective: For transradial amputees, robotic prosthetic hands promise to regain the capability to perform daily living activities. Current control methods based on physiological signals such as electromyography (EMG) are prone to yielding poor inference outcomes due to motion artifacts, muscle fatig...

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Detaylı Bibliyografya
Asıl Yazarlar: Mehrshad Zandigohar, Mo Han, Mohammadreza Sharif, Sezen Yağmur Günay, Mariusz P. Furmanek, Mathew Yarossi, Paolo Bonato, Cagdas Onal, Taşkın Padır, Deniz Erdoğmuş, Gunar Schirner
Materyal Türü: Makale
Dil:English
Baskı/Yayın Bilgisi: Frontiers Media S.A. 2024-02-01
Seri Bilgileri:Frontiers in Robotics and AI
Konular:
dataset
EMG
grasp detection
neural networks
robotic prosthetic hand
Online Erişim:https://www.frontiersin.org/articles/10.3389/frobt.2024.1312554/full

Internet

https://www.frontiersin.org/articles/10.3389/frobt.2024.1312554/full

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